Word Prediction App: N-gram Model for Text Prediction

The Challenge:

• People need faster ways to enter text on mobile devices
• Predictive text can significantly reduce typing effort
• Modern keyboards need smart, efficient prediction algorithms

Our Solution:

• A fast, memory-efficient next word prediction model
• Based on N-gram analysis of large text corpora
• Uses a sophisticated backoff model for accurate predictions
• Deployed as a user-friendly Shiny application

INPUT → PREPROCESSING → PREDICTION

Quadgram → Trigram → Bigram → Unigram

Key Features:

• Hierarchical backoff model
• Fast lookup data structures
• Confidence scoring
• Clean text preprocessing

Application Features:

• Real-time next word prediction
• Simple, intuitive user interface
• Click-to-add predicted words
• Displays prediction confidence and model used
• Optimized for speed and responsiveness

How to use it: 1. Type text in the input box 2. View the top predictions 3. Click on a predicted word to add it 4. See which model made the prediction

Model Performance:

• Prediction time: <50ms on average
• Memory usage: Optimized for mobile/browser environments
• Accuracy: ~28% Top-1, ~45% Top-3 on test corpus

Future Improvements:

• User-specific adaptation to personal writing style
• Domain-specific models (email, social, academic)
• Integration with mobile keyboard frameworks
• Hybrid neural-statistical models for improved accuracy

Conclusion: A practical, efficient solution for real-world text prediction needs.